Keywords

Introduction

Various clinical indexes are used in clinical practice throughout the world to assess critically ill patients and to predict their outcome. Some of the most popular tools, however, have not had proper validation in populations different from those in which the tools were developed. We review our experience at a critical care unit in Mendoza, Argentina, with the Logistic Organ Dysfunction (LOD) system, developed by LeGall in 1996.

Objective

To evaluate the ability of the LOD system to predict total patient mortality.

Materials and methods

We prospectively evaluated all patients admitted to the critical care unit (CCU) of our 200-bed tertiary care hospital, from July of 1999 to August of 2000. Patients younger than 16 years of age and those whose admission to the CCU was shorter than 24 hours, were excluded. Clinical data collected included: age, sex, admitting diagnosis, length of stay, physiological variables and Glasgow coma scale. Laboratory data included: WBC, BUN, creatinine, total bilirrubin, prothrombin time, serum sodium and potassium and arterial pO2. We also documented need for mechanical ventilation, FIO2, and final outcome at time of discharge (dead or alive).

The chi-square test was used for qualitative variables, and ANOVA was used for continuous variables. A P < 0.05 was assigned statistical significance. Results were expressed as percentages, confidence intervals (CI 95%), means and standard deviations (SD). We analysed the observed mortality vs predicted mortality ratio (OM/PM), sensitivity, specificity and percentage of accurate prediction for a cut off point of 50% of probability of death. The Receptor Operator Curve (ROC) was used to determine the LOD's power of discrimination. The 'Goodness of Fit' test (Hosmer–Lemeshow) was applied to evaluate the calibration in our population.

Results

448 patients were included in the study. Thirty percent of patients who met LOD criteria developed severe multiple organ failure (MOF). The average LOD score was 1.83 ± 2.26 with a predicted probability of death of 9.47 ± 11.30%. The global mortality rate was 17.6% (80 patients); therefore the OM/PM ratio was 1.85. The global percentage of accurate prediction was 85.71% for a cut off point of 50% of probability of death. The area under the ROC was 0.834 (CI 95% 0.781–0.886). The Hosmer–Lemeshhow test showed a GOF of 20.59.

Conclusion

In our hands, the LOD system proved to be capable of discriminating among critically ill patients those likely to die. It, however, did not prove an appropriate calibation in our population of patients. We emphasize the need for proper regional validation in populations different from those in which the tools were developed.